sg_uv_index

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful context beyond the function name: the hourly frequency and the interpretation scale (0-2 Low, etc.). It does not detail data source or update timing, but for a simple 0-parameter read tool, this is sufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two short sentences. The first states the action and resource, the second gives the value scale. Every word earns its place, no fluff or repetition of the schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (0 params, no output schema, no annotations), the description covers the core semantics: what it returns (hourly UV index readings) and how to interpret them. It does not specify the exact output structure (e.g., array of timestamps), but this is a minor gap for such a straightforward tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and the schema coverage is 100% (trivially). The description does not need to explain parameters. Baseline for 0 parameters is 4, and the description adds no unnecessary parameter-related info.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb and resource: 'Get Singapore UV index readings (hourly)'. This clearly identifies the tool's function and distinguishes it from sibling tools like sg_weather or sg_air_quality, which focus on different data types.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description makes the use case obvious (retrieving UV index readings), providing clear context within the Singapore data tool ecosystem. However, it does not explicitly state when not to use it or mention alternatives, so it falls just short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.